Geosocial intelligence: assisting flood

mitigation

Robert Ogie Smart Infrastructure Facility, University of Wollongong

May, 2016

Source: Adi Weda EPA

Source: Twitter @ TMCPoldaMetro

Flood exposure in coastal mega-cities

• 890 million city residents are currently exposed to natural disasters, including

flooding

• Average annual global flood losses: $6 billion (2005) $1 trillion (2050)

• Climate change + subsiding land + population explosion + rapid urbanization = increased exposure to flood hazards The situation is far more complicated in developing nations • Climate change + subsiding land + population explosion + rapid urbanization + infrastructure fragility + human factors (e.g. trash dumps) + data scarcity = increased exposure to flood hazards

Broken Canal Wall

Broken Canal Wall

Pilot Study 2014/2015 60 days: 100,000 #flood tweets 1,000 confirmed reports 69,000 users 2.2m Twitter impressions

www.petajakarta.org

Proactive response to flood disasters • How can we make more informed decision related to the use of pumps

and floodgates to control floods, such that excessive pressure created by accumulating floodwater does not result in structural failure and flooding due to infrastructure fragility?

• How can we identify the floodgates that are most vulnerable to failure or

damage due the impact of flood waters, so that limited resources can be judiciously allocated for maintenance and flood preparedness?

• How can we identify the pumping stations that are most vulnerable to failure due to trash blockage, so that limited resources can be judiciously allocated for maintenance and flood preparedness?

628 edges representing rivers, streams, and canals in Jakarta. Total geometric length of waterways is 1092 km. 560 nodes with 96 of those representing infrastructure (55 pumps, 30 floodgates, and 11 flood gauges) 464 network junctions (e.g., river confluences)

Ogie, R., Holderness, T., Dunbar, M. and Turpin, E., 2016. Spatio-topological network analysis of hydrological infrastructure as a decision support tool for flood mitigation in coastal mega-cities. Environment and Planning B: Planning and Design, p.0265813516637608.

Application case 1

Application case 1 continues……

𝐹𝐹𝐼 = 𝐸∗𝑆𝑅

(1) 𝐸 = ∑ 𝑙𝑖𝑛

𝑖=1 (2) 𝑆 = 1

𝐶𝑔 (3)

𝑅 = 𝑅𝑠 + ∑ 𝑐𝑖

𝑙𝑖∗𝑏𝑖𝑚𝑖=0 (4)

𝐻𝐼𝐹𝐹𝐼 = ∑ 𝑙𝑖𝑛𝑖=1

𝐶𝑔(𝑅𝑠+∑𝑐𝑖

𝑙𝑖∗𝑏𝑖𝑚𝑖=0 )

(5)

Application case 2: Vulnerability analysis of hydrological infrastructure to flood hazards

Notation FVI = Flood Vulnerability Index E = Exposure S = Susceptibility R = Resilience HIFVI = Hydrological Infrastructure Flood Vulnerability Index

A

G1

G3

G2

B

G

D

E

C

F

Flow

dire

ctio

n

VH= Very High (0.8 -1.0), M = Medium (0.4 - 0.6), L = Low (0.2 -0.4), and VL = Very Low (0 -0.2).

Name of floodgate Susceptibility Resilience Exposure HIFVI Ranking

Sunter C 1.00 0.45 199.89 1.000 VH Ciliwung Lama 1.00 0.05 133.65 0.922 VH Kebon Baru 1.00 0.00 122.59 0.890 VH Muara Angke 0.50 0.43 203.95 0.519 M Cakung Drainase 0.33 0.00 164.23 0.398 L Karet 2 0.50 0.39 150.31 0.392 L Pasar Ikan 0.25 0.51 307.40 0.371 L Hailai 0.50 0.78 169.77 0.347 L Istiqlal 0.33 0.13 160.47 0.345 L Tangki 0.50 0.94 164.02 0.308 L Jembatan Merah 0.25 0.10 163.09 0.269 L Citra Land 0.33 0.75 153.79 0.213 L Cengkareng Drain 0.25 0.00 101.23 0.184 VL Pulogadung 0.17 0.00 143.50 0.174 VL Ancol 0.20 0.52 176.82 0.170 VL Pekapuran 0.20 0.64 170.12 0.151 VL 8 0.13 0.26 151.23 0.109 VL Sogo 0.50 0.53 36.24 0.086 VL Poglar 0.33 0.00 33.81 0.082 VL Warung Pedok 0.50 0.00 12.81 0.046 VL Manggarai 0.33 0.19 21.79 0.044 VL Setia Budi 0.33 0.15 19.70 0.041 VL Minangkabau 0.50 0.64 15.94 0.035 VL Kampung Gusti 0.50 6.25 34.29 0.017 VL Kalimati 0.50 0.00 3.04 0.011 VL Honda 0.17 0.00 6.84 0.008 VL Duri 0.33 0.00 3.09 0.007 VL Karet 0.25 62.26 150.34 0.004 VL Sunter Utara 0.25 0.00 0.92 0.002 VL Kali Cideng 0.33 5524.27 150.35 0.000 VL

Application case 3: Vulnerability of pumping stations to trash blockage

𝐹𝐹𝐼 = 𝐸∗𝑆𝑅

(1) 𝐸 = ∑ (𝑙𝑖∗ 𝑤𝑖)𝑛

𝑖=1 (2) 𝑙𝑖𝑒 = 𝑑𝑖 + 𝑙𝑖 − 𝑑𝑖 ∗ 𝑑𝑖 𝑙𝑖� (3) 𝐸 = ∑ (𝑙𝑖𝑒 ∗ 𝑤𝑖)𝑛

𝑖=1 (4) 𝑆 = 1

𝐶𝑔 (5)

𝑅 = 𝑅𝑚 + (𝑛 − 1) (6) 𝑇𝑇𝐹𝐼𝑙𝑙𝑐𝑙𝑙 = ∑ (𝑙𝑖

𝑒∗𝑤𝑖)𝑛𝑖=1

𝐶𝑔(𝑅𝑚+(𝑛−1)) (7)

𝑇𝑇𝐹𝐼𝐺𝑙𝑙𝑏𝑙𝑙 =∑ (𝑙𝑖,𝑡𝑡𝑡𝑡𝑙

𝑒 ∗𝑤𝑖)𝑛𝑖=1𝐶𝑔(𝑅𝑚+(𝑛−1))

(8)

Direction of Flow

P2P1

Section 1 Section 2 Section 3

356511401

57453438445437672869201533466

614318589

42411471305329101950313673

2752258

47635666136251173955264

6848166470602

2412225

2159324923

Local TBVI Global TBVI

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 50000 100000 150000 200000 250000

Glo

bal

TB

VI

Exposure, E

Way forward

• Move network analysis from local to global flood condition

• Develop flood inundation model (DATA?)

Key research questions?

• How does one foster “odd time” sensing?

• How can manipulative effect and truthfulness be checked?

• How many human sensors can cover the city? How can one ensure area coverage requirement is always met?

• Standardisation of crowdsensed flood height

• How can citizens be motivated to participate proactively in sensing flood?

• Does absence of tweets always indicate no floods; what is the check?

• Should participants be given incentives?

• What type of incentives?

Conclusion

Q& A